Fine-scale flight strategies of gulls in urban airflows indicate risk and reward in city living

Birds modulate their flight paths in relation to regional and global airflows in order to reduce their travel costs. Birds should also respond to fine-scale airflows, although the incidence and value of this remains largely unknown. We resolved the three-dimensional trajectories of gulls flying along a built-up coastline, and used computational fluid dynamic models to examine how gulls reacted to airflows around buildings. Birds systematically altered their flight trajectories with wind conditions to exploit updraughts over features as small as a row of low-rise buildings. This provides the first evidence that human activities can change patterns of space-use in flying birds by altering the profitability of the airscape. At finer scales still, gulls varied their position to select a narrow range of updraught values, rather than exploiting the strongest updraughts available, and their precise positions were consistent with a strategy to increase their velocity control in gusty conditions. Ultimately, strategies such as these could help unmanned aerial vehicles negotiate complex airflows. Overall, airflows around fine-scale features have profound implications for flight control and energy use, and consideration of this could lead to a paradigm-shift in the way ecologists view the urban environment.This article is part of the themed issue ‘Moving in a moving medium: new perspectives on flight’.     

The effect of bait air broadcasting by unmanned aerial vehicles on the ant community diversity

To explore the control effect of bait broadcasting by unmanned aerial vehicles (UAVs) on the imported fire ant Solenopsis invicta and evaluate its impact on biodiversity, we tested the drop flow rate and broadcasting evenness of fire ant baits with bait exit hatch sizes, as well as the dynamics of fire ants and other ants when different amounts of bait were used. The amount of bait applied per hectare was 6000–15,000 g in orchards. Fourteen days after broadcasting, the control effect of broadcasting 12,000 g and 15,000 g bait per hectare on active mounds and workers reached 90%, which was significantly higher than that achieved with 6000 g and 9000 g. After the application of bait, the number and species of other ants decreased and then increased; this was reflected in changes in the Shannon–Wiener index (H′), Pielou evenness index (E) and Simpson dominance index (C). The results of this study suggest that broadcasting bait by UAVs can achieve good control of S. invicta, and a reduction in native ant diversity can be achieved in the short term.     

森林转基因林木抽样策略的研究

转基因技术加快了林木遗传改良的进程。由于转基因林木存在潜在的生态风险,有必要对森林中转基因林木的分布等情况进行监测。基于无人机(unmanned aerial vehicles,UAV)获取的森林平面影像,提出了真实地形下森林转基因林木抽样监测的策略。首先根据检验参数来确定需要抽样的样本数,然后改进了两种算法分别进行不规则区域内常规的和有孔洞情况下的均匀抽样。与之前的抽样方法相比,本方法提供了更好的抽样准确性和均匀性,更适应森林区域的实际情况。     

Automatic wheat ear counting using machine learning based on RGB UAV imagery

In wheat (Triticum aestivum L) and other cereals, the number of ears per unit area is one of the main yield‐determining components. An automatic evaluation of this parameter may contribute to the advance of wheat phenotyping and monitoring. There is no standard protocol for wheat ear counting in the field, and moreover it is time consuming. An automatic ear‐counting system is proposed using machine learning techniques based on RGB (red, green, blue) images acquired from an unmanned aerial vehicle (UAV). Evaluation was performed on a set of 12 winter wheat cultivars with three nitrogen treatments during the 2017–2018 crop season. The automatic system uses a frequency filter, segmentation and feature extraction, with different classification techniques, to discriminate wheat ears in micro‐plot images. The relationship between the image‐based manual counting and the algorithm counting exhibited high levels of accuracy and efficiency. In addition, manual ear counting was conducted in the field for secondary validation. The correlations between the automatic and the manual in‐situ ear counting with grain yield were also compared. Correlations between the automatic ear counting and grain yield were stronger than those between manual in‐situ counting and GY, particularly for the lower nitrogen treatment. Methodological requirements and limitations are discussed.     

Fast R-CNN深度学习和无人机遥感相结合在松材线虫病监测中的初步应用研究

松材线虫病因其破坏性强、传播速度快和防治难度大等特点,严重威胁着我国的松林资源.及时发现、定位和清理病死松树是控制松材线虫病蔓延的有效手段.本研究利用小型无人机获得松材线虫病疫点的可见光和多光谱的航摄影像.根据松树针叶颜色变化,将松材线虫Bursaphelenchus xylophilus侵染的松树分为病树和枯死树两种...     

无人机航测在风景园林中的应用研究

近年来随着民用无人机的普及,无人机开始越来越多地应用于风景园林领域中。但目前大多数应用还停留在基础的航拍层面,对于应用潜力更大的航测层面,在风景园林行业中的应用相对较少,也更鲜为人知,现有研究更多聚焦于具体案例的应用方面,未能对其进行系统的认知和介绍。简要介绍无人机航测与遥感系统的构成及常见传感器类型,通过文献综合、项目实践等方法,系统地整理了国内外无人机航测相关的研究与应用进展,进而总结出无人机航测在风景园林中的应用可分为传统航测、倾斜摄影、多种传感器遥感3个方面。最后指出传统航测发展最为成熟,短时间内推广应用的可能性最大;倾斜摄影效率最高;多种传感器遥感未来开发潜力最大。以期对今后无人机在风景园林中的应用与研究有所启发。     

无人机和地面相结合的自然保护地生物多样性监测技术与实践

无人机技术的运用为自然保护地生物多样性监测与研究带来了新的机遇和变革。然而, 对自然保护地主要保护对象的关注不足, 导致了无人机和地面相结合的监测技术尚未形成。为更好地发挥多种调查监测技术的各自优势, 为自然保护地生物多样性管护和监测提供支撑, 我们总结了国内外已开展的无人机和地面相结合的监测工作进展, 梳理了我国不同类型自然保护地生物多样性保护管理和监测的需求。总的来看, 不同类型自然保护地的主要保护对象围绕在生态系统、物种、遗址遗迹等或由上述要素构成的景观资源上; 管理目标定位则集中在保护、恢复、科研、宣教、游憩和可持续发展等方面。基于上述需求, 我们归纳提出了包括图像识别与分类解译、数据反演与格局分析、数字建模与地表测量、巡护巡检4个类别共计14个专题的无人机和地面相结合的监测技术方案, 明确了监测时期与频次、监测指标、监测技术的结合途径以及数据后处理方法等。同时, 我们在三江并流世界遗产地云岭片区内选择植物识别、植被长势、景观格局、地表测量以及执法检查等技术专题开展了应用试验。在技术方案取得良好验证结果的同时, 实现了对自然保护地生物多样性保护和管理的技术支撑, 为未来自然保护地精细化管理提供了技术储备。     

Automated Flight Test and System Identification for Rotary Wing Small Aerial Platform Using Frequency Responses Analysis

This paper proposes an autopilot system that can be used to control the small scale rotorcraft during the flight test for linear-frequency-domain system identification. The input frequency-sweep is generated automatically as part of the autopilot control command. Therefore the bandwidth coverage and consistency of the frequency-sweep are guaranteed to produce high quality data for system identification. Beside that, we can set the safety parameters during the flight test （maximum roll/pitch value, minimum altitude, etc.） so the safety of the whole flight test is guaranteed. This autopilot system is validated using hardware in the loop simulator for hover flight condition.